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For: Kassianos A, Emery J, Murchie P, Walter F. Smartphone applications for melanoma detection by community, patient and generalist clinician users: a review. Br J Dermatol 2015;172:1507-18. [DOI: 10.1111/bjd.13665] [Cited by in Crossref: 83] [Cited by in F6Publishing: 58] [Article Influence: 11.9] [Reference Citation Analysis]
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3 Majtner T, Yildirim-yayilgan S, Hardeberg JY. Efficient Melanoma Detection Using Texture-Based RSurf Features. In: Campilho A, Karray F, editors. Image Analysis and Recognition. Cham: Springer International Publishing; 2016. pp. 30-7. [DOI: 10.1007/978-3-319-41501-7_4] [Cited by in Crossref: 5] [Cited by in F6Publishing: 1] [Article Influence: 0.8] [Reference Citation Analysis]
4 Jinnai S, Yamazaki N, Hirano Y, Sugawara Y, Ohe Y, Hamamoto R. The Development of a Skin Cancer Classification System for Pigmented Skin Lesions Using Deep Learning. Biomolecules. 2020;10. [PMID: 32751349 DOI: 10.3390/biom10081123] [Cited by in Crossref: 14] [Cited by in F6Publishing: 12] [Article Influence: 7.0] [Reference Citation Analysis]
5 Sar-Graycar L, Rotemberg VM, Matsoukas K, Halpern AC, Marchetti MA, Hay JL. Interactive skin self-examination digital platforms for the prevention of skin cancer: A narrative literature review. J Am Acad Dermatol 2021;84:1459-68. [PMID: 32659420 DOI: 10.1016/j.jaad.2020.07.014] [Reference Citation Analysis]
6 Charbonneau DH, Hightower S, Katz A, Zhang K, Abrams J, Senft N, Beebe-Dimmer JL, Heath E, Eaton T, Thompson HS. Smartphone apps for cancer: A content analysis of the digital health marketplace. Digit Health 2020;6:2055207620905413. [PMID: 32110428 DOI: 10.1177/2055207620905413] [Cited by in Crossref: 14] [Cited by in F6Publishing: 6] [Article Influence: 7.0] [Reference Citation Analysis]
7 Smith KA, Zhou L, Watzlaf VJM. User Authentication in Smartphones for Telehealth. Int J Telerehabil 2017;9:3-12. [PMID: 29238444 DOI: 10.5195/ijt.2017.6226] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 1.8] [Reference Citation Analysis]
8 Jaworek-korjakowska J, Kleczek P. eSkin: Study on the Smartphone Application for Early Detection of Malignant Melanoma. Wireless Communications and Mobile Computing 2018;2018:1-11. [DOI: 10.1155/2018/5767360] [Cited by in Crossref: 8] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
9 Chuchu N, Takwoingi Y, Dinnes J, Matin RN, Bassett O, Moreau JF, Bayliss SE, Davenport C, Godfrey K, O'Connell S, Jain A, Walter FM, Deeks JJ, Williams HC; Cochrane Skin Cancer Diagnostic Test Accuracy Group. Smartphone applications for triaging adults with skin lesions that are suspicious for melanoma. Cochrane Database Syst Rev 2018;12:CD013192. [PMID: 30521685 DOI: 10.1002/14651858.CD013192] [Cited by in Crossref: 31] [Cited by in F6Publishing: 22] [Article Influence: 7.8] [Reference Citation Analysis]
10 Austin RE. Commentary on: Patient Satisfaction With an Early Smartphone-Based Cosmetic Surgery Postoperative Follow-Up. Aesthet Surg J 2017;38:110-3. [PMID: 28605405 DOI: 10.1093/asj/sjx107] [Reference Citation Analysis]
11 Thissen M, Udrea A, Hacking M, von Braunmuehl T, Ruzicka T. mHealth App for Risk Assessment of Pigmented and Nonpigmented Skin Lesions-A Study on Sensitivity and Specificity in Detecting Malignancy. Telemed J E Health 2017;23:948-54. [PMID: 28562195 DOI: 10.1089/tmj.2016.0259] [Cited by in Crossref: 27] [Cited by in F6Publishing: 22] [Article Influence: 5.4] [Reference Citation Analysis]
12 Singh N, Gupta SK. Recent advancement in the early detection of melanoma using computerized tools: An image analysis perspective. Skin Res Technol 2019;25:129-41. [PMID: 30030916 DOI: 10.1111/srt.12622] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
13 Chao E, Meenan CK, Ferris LK. Smartphone-Based Applications for Skin Monitoring and Melanoma Detection. Dermatol Clin. 2017;35:551-557. [PMID: 28886812 DOI: 10.1016/j.det.2017.06.014] [Cited by in Crossref: 43] [Cited by in F6Publishing: 22] [Article Influence: 8.6] [Reference Citation Analysis]
14 Ngoo A, Finnane A, Mcmeniman E, Tan J, Janda M, Soyer HP. Efficacy of smartphone applications in high-risk pigmented lesions. Australas J Dermatol 2018;59:e175-82. [DOI: 10.1111/ajd.12599] [Cited by in Crossref: 25] [Cited by in F6Publishing: 21] [Article Influence: 5.0] [Reference Citation Analysis]
15 Murchie P, Allan JL, Brant W, Dennis M, Hall S, Masthoff J, Walter FM, Johnston M. Total skin self-examination at home for people treated for cutaneous melanoma: development and pilot of a digital intervention. BMJ Open 2015;5:e007993. [PMID: 26251412 DOI: 10.1136/bmjopen-2015-007993] [Cited by in F6Publishing: 7] [Reference Citation Analysis]
16 Zortea M, Flores E, Scharcanski J. A simple weighted thresholding method for the segmentation of pigmented skin lesions in macroscopic images. Pattern Recognition 2017;64:92-104. [DOI: 10.1016/j.patcog.2016.10.031] [Cited by in Crossref: 26] [Cited by in F6Publishing: 4] [Article Influence: 5.2] [Reference Citation Analysis]
17 Mar VJ, Scolyer RA, Long GV. Computer-assisted diagnosis for skin cancer: have we been outsmarted? Lancet 2017;389:1962-4. [PMID: 28534744 DOI: 10.1016/S0140-6736(17)31285-0] [Cited by in Crossref: 7] [Cited by in F6Publishing: 2] [Article Influence: 1.8] [Reference Citation Analysis]
18 Rubagumya F, Nyagabona SK, Longombe AN, Manirakiza A, Ngowi J, Maniragaba T, Sabushimike D, Urusaro S, Ndoli DA, Dharsee N, Mwaiselage J, Mavura D, Hanna TP, Hammad N. Feasibility Study of a Smartphone Application for Detecting Skin Cancers in People With Albinism. JCO Glob Oncol 2020;6:1370-5. [PMID: 32903120 DOI: 10.1200/GO.20.00264] [Reference Citation Analysis]
19 Augustin M, Wimmer J, Biedermann T, Blaga R, Dierks C, Djamei V, Elmer A, Elsner P, Enk A, Gass S, Henningsen M, Hofman-wellenhof R, von Kiedrowski R, Kunz H, Liebram C, Navarini A, Otten M, Reusch M, Schüller C, Zink A, Strömer K. Praxis der Teledermatologie. JDDG: Journal der Deutschen Dermatologischen Gesellschaft 2018;16:6-57. [DOI: 10.1111/ddg.13512] [Cited by in Crossref: 15] [Cited by in F6Publishing: 10] [Article Influence: 3.8] [Reference Citation Analysis]
20 Habgood E, Walter FM, O'Hare E, McIntosh J, McCormack C, Emery JD. Using an electronic self-completion tool to identify patients at increased risk of melanoma in Australian primary care. Australas J Dermatol 2020;61:231-6. [PMID: 32050041 DOI: 10.1111/ajd.13244] [Cited by in Crossref: 2] [Article Influence: 1.0] [Reference Citation Analysis]
21 Millenson ML, Baldwin JL, Zipperer L, Singh H. Beyond Dr. Google: the evidence on consumer-facing digital tools for diagnosis. Diagnosis (Berl) 2018;5:95-105. [PMID: 30032130 DOI: 10.1515/dx-2018-0009] [Cited by in Crossref: 26] [Cited by in F6Publishing: 17] [Article Influence: 6.5] [Reference Citation Analysis]
22 Kong FW, Horsham C, Ngoo A, Soyer HP, Janda M. Review of smartphone mobile applications for skin cancer detection: what are the changes in availability, functionality, and costs to users over time? Int J Dermatol 2021;60:289-308. [PMID: 32880938 DOI: 10.1111/ijd.15132] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
23 Finnane A, Soyer H. Smartphone diagnosis of skin cancer: there's not yet an app for that. Br J Dermatol 2015;172:1474-5. [DOI: 10.1111/bjd.13842] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 0.6] [Reference Citation Analysis]
24 Chu YS, An HG, Oh BH, Yang S. Artificial Intelligence in Cutaneous Oncology. Front Med (Lausanne) 2020;7:318. [PMID: 32754606 DOI: 10.3389/fmed.2020.00318] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
25 Ersser S, Effah A, Dyson J, Kellar I, Thomas S, Mcnichol E, Caperon E, Hewitt C, Muinonen‐martin A. Effectiveness of interventions to support the early detection of skin cancer through skin self‐examination: a systematic review and meta‐analysis. Br J Dermatol 2019;180:1339-47. [DOI: 10.1111/bjd.17529] [Cited by in Crossref: 8] [Cited by in F6Publishing: 4] [Article Influence: 2.7] [Reference Citation Analysis]
26 Po Harvey Chin Y, Hsin Huang I, Yu Hou Z, Yu Chen P, Bassir F, Han Wang H, Ting Lin Y, Chuan Jack Li Y. User satisfaction with a smartphone-compatible, artificial intelligence-based cutaneous pigmented lesion evaluator. Comput Methods Programs Biomed 2020;195:105649. [PMID: 32750631 DOI: 10.1016/j.cmpb.2020.105649] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
27 Osei E, Mashamba-Thompson TP. Mobile health applications for disease screening and treatment support in low-and middle-income countries: A narrative review. Heliyon 2021;7:e06639. [PMID: 33869857 DOI: 10.1016/j.heliyon.2021.e06639] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 5.0] [Reference Citation Analysis]
28 Marek AJ, Chu EY, Ming ME, Khan ZA, Kovarik CL. Impact of a smartphone application on skin self-examination rates in patients who are new to total body photography: A randomized controlled trial. J Am Acad Dermatol 2018;79:564-7. [PMID: 29438760 DOI: 10.1016/j.jaad.2018.02.025] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
29 Zink A, Kolbinger A, Leibl M, Léon Suarez I, Gloning J, Merkel C, Winkler J, Biedermann T, Ring J, Eberlein B. Teledermatoskopie mittels Smartphone: Zuverlässige Hilfe bei der Diagnostik von Hautläsionen? Hautarzt 2017;68:890-5. [DOI: 10.1007/s00105-017-4042-0] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 1.4] [Reference Citation Analysis]
30 Freeman K, Dinnes J, Chuchu N, Takwoingi Y, Bayliss SE, Matin RN, Jain A, Walter FM, Williams HC, Deeks JJ. Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies. BMJ 2020;368:m127. [PMID: 32041693 DOI: 10.1136/bmj.m127] [Cited by in Crossref: 46] [Cited by in F6Publishing: 31] [Article Influence: 23.0] [Reference Citation Analysis]
31 Adam R, McMichael D, Powell D, Murchie P. Publicly available apps for cancer survivors: a scoping review. BMJ Open 2019;9:e032510. [PMID: 31575584 DOI: 10.1136/bmjopen-2019-032510] [Cited by in Crossref: 17] [Cited by in F6Publishing: 7] [Article Influence: 5.7] [Reference Citation Analysis]
32 Phillips M, Greenhalgh J, Marsden H, Palamaras I. Detection of Malignant Melanoma Using Artificial Intelligence: An Observational Study of Diagnostic Accuracy. Dermatol Pract Concept 2020;10:e2020011. [PMID: 31921498 DOI: 10.5826/dpc.1001a11] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
33 Phillips M, Marsden H, Jaffe W, Matin RN, Wali GN, Greenhalgh J, McGrath E, James R, Ladoyanni E, Bewley A, Argenziano G, Palamaras I. Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions. JAMA Netw Open 2019;2:e1913436. [PMID: 31617929 DOI: 10.1001/jamanetworkopen.2019.13436] [Cited by in Crossref: 34] [Cited by in F6Publishing: 28] [Article Influence: 11.3] [Reference Citation Analysis]
34 Kostopoulos SA, Asvestas PA, Kalatzis IK, Sakellaropoulos GC, Sakkis TH, Cavouras DA, Glotsos DT. Adaptable pattern recognition system for discriminating Melanocytic Nevi from Malignant Melanomas using plain photography images from different image databases. Int J Med Inform 2017;105:1-10. [PMID: 28750902 DOI: 10.1016/j.ijmedinf.2017.05.016] [Cited by in Crossref: 12] [Cited by in F6Publishing: 4] [Article Influence: 2.4] [Reference Citation Analysis]
35 de Carvalho TM, Noels E, Wakkee M, Udrea A, Nijsten T. Development of Smartphone Apps for Skin Cancer Risk Assessment: Progress and Promise. JMIR Dermatol 2019;2:e13376. [DOI: 10.2196/13376] [Cited by in Crossref: 7] [Cited by in F6Publishing: 2] [Article Influence: 2.3] [Reference Citation Analysis]
36 Raphael AP, Soyer HP. Automated diagnosis: shedding the light on skin cancer. Br J Dermatol 2018;178:331-3. [PMID: 29441560 DOI: 10.1111/bjd.16219] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.8] [Reference Citation Analysis]
37 Udrea A, Mitra GD, Costea D, Noels EC, Wakkee M, Siegel DM, de Carvalho TM, Nijsten TEC. Accuracy of a smartphone application for triage of skin lesions based on machine learning algorithms. J Eur Acad Dermatol Venereol 2020;34:648-55. [PMID: 31494983 DOI: 10.1111/jdv.15935] [Cited by in Crossref: 20] [Cited by in F6Publishing: 13] [Article Influence: 6.7] [Reference Citation Analysis]
38 Voss RK, Woods TN, Cromwell KD, Nelson KC, Cormier JN. Improving outcomes in patients with melanoma: strategies to ensure an early diagnosis. Patient Relat Outcome Meas 2015;6:229-42. [PMID: 26609248 DOI: 10.2147/PROM.S69351] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.4] [Reference Citation Analysis]
39 Alves J, Moreira D, Alves P, Rosado L, Vasconcelos MJM. Automatic Focus Assessment on Dermoscopic Images Acquired with Smartphones. Sensors (Basel) 2019;19:E4957. [PMID: 31739464 DOI: 10.3390/s19224957] [Cited by in Crossref: 10] [Cited by in F6Publishing: 3] [Article Influence: 3.3] [Reference Citation Analysis]
40 Rat C, Hild S, Rault Sérandour J, Gaultier A, Quereux G, Dreno B, Nguyen JM. Use of Smartphones for Early Detection of Melanoma: Systematic Review. J Med Internet Res 2018;20:e135. [PMID: 29653918 DOI: 10.2196/jmir.9392] [Cited by in Crossref: 42] [Cited by in F6Publishing: 33] [Article Influence: 10.5] [Reference Citation Analysis]
41 Surówka G, Ogorzalek M. Resolution invariant wavelet features of melanoma studied by SVM classifiers. PLoS One 2019;14:e0211318. [PMID: 30726260 DOI: 10.1371/journal.pone.0211318] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 1.3] [Reference Citation Analysis]
42 Moshi MR, Tooher R, Merlin T. SUITABILITY OF CURRENT EVALUATION FRAMEWORKS FOR USE IN THE HEALTH TECHNOLOGY ASSESSMENT OF MOBILE MEDICAL APPLICATIONS: A SYSTEMATIC REVIEW. Int J Technol Assess Health Care 2018;34:464-75. [PMID: 30201060 DOI: 10.1017/S026646231800051X] [Cited by in Crossref: 20] [Cited by in F6Publishing: 11] [Article Influence: 5.0] [Reference Citation Analysis]
43 Marek AJ, Chu EY, Ming ME, Kovarik CL. Assessment of smartphone applications for total body digital photography-guided skin exams by patients. J Am Acad Dermatol 2016;75:1063-1064.e1. [PMID: 27745634 DOI: 10.1016/j.jaad.2016.06.005] [Cited by in Crossref: 8] [Cited by in F6Publishing: 5] [Article Influence: 1.6] [Reference Citation Analysis]
44 McKay FH, Slykerman S, Dunn M. The App Behavior Change Scale: Creation of a Scale to Assess the Potential of Apps to Promote Behavior Change. JMIR Mhealth Uhealth 2019;7:e11130. [PMID: 30681967 DOI: 10.2196/11130] [Cited by in Crossref: 35] [Cited by in F6Publishing: 19] [Article Influence: 11.7] [Reference Citation Analysis]
45 Sayed L, Akhtar N. A Simple Method to Monitor Skin Cancer. Plast Reconstr Surg Glob Open 2016;4:e666. [PMID: 27257596 DOI: 10.1097/GOX.0000000000000615] [Reference Citation Analysis]
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47 Ngoo A, Finnane A, Mcmeniman E, Soyer HP, Janda M. Fighting Melanoma with Smartphones: A Snapshot of Where We are a Decade after App Stores Opened Their Doors. International Journal of Medical Informatics 2018;118:99-112. [DOI: 10.1016/j.ijmedinf.2018.08.004] [Cited by in Crossref: 18] [Cited by in F6Publishing: 11] [Article Influence: 4.5] [Reference Citation Analysis]
48 Cazzaniga S, Castelli E, Di Landro A, Di Mercurio M, Imberti G, Locatelli GA, Raponi F, Vezzoli P, Gambini D, Damiani G, Zucchi A, Naldi L. Mobile teledermatology for melanoma detection: Assessment of the validity in the framework of a population-based skin cancer awareness campaign in northern Italy. J Am Acad Dermatol 2019;81:257-60. [PMID: 30797846 DOI: 10.1016/j.jaad.2019.02.036] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
49 Zaidan AA, Zaidan BB, Albahri OS, Alsalem MA, Albahri AS, Yas QM, Hashim M. A review on smartphone skin cancer diagnosis apps in evaluation and benchmarking: coherent taxonomy, open issues and recommendation pathway solution. Health Technol 2018;8:223-38. [DOI: 10.1007/s12553-018-0223-9] [Cited by in Crossref: 49] [Cited by in F6Publishing: 11] [Article Influence: 12.3] [Reference Citation Analysis]
50 Mills K, Emery J, Lantaff R, Radford M, Pannebakker M, Hall P, Burrows N, Williams K, Saunders CL, Murchie P, Walter FM. Protocol for the melatools skin self-monitoring trial: a phase II randomised controlled trial of an intervention for primary care patients at higher risk of melanoma. BMJ Open 2017;7:e017934. [PMID: 29187412 DOI: 10.1136/bmjopen-2017-017934] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
51 Waterhouse DJ, Fitzpatrick CRM, Pogue BW, O’connor JPB, Bohndiek SE. A roadmap for the clinical implementation of optical-imaging biomarkers. Nat Biomed Eng 2019;3:339-53. [DOI: 10.1038/s41551-019-0392-5] [Cited by in Crossref: 15] [Cited by in F6Publishing: 18] [Article Influence: 5.0] [Reference Citation Analysis]
52 Kostopoulos S, Ravazoula P, Asvestas P, Kalatzis I, Xenogiannopoulos G, Cavouras D, Glotsos D. Development of a Reference Image Collection Library for Histopathology Image Processing, Analysis and Decision Support Systems Research. J Digit Imaging 2017;30:287-95. [PMID: 28083826 DOI: 10.1007/s10278-017-9947-8] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
53 Urner E, Delavy M, Catarino R, Viviano M, Meyer-Hamme U, Benski AC, Jinoro J, Heriniainasolo JL, Undurraga M, De Vuyst H, Combescure C, Vassilakos P, Petignat P. A Smartphone-Based Approach for Triage of Human Papillomavirus-Positive Sub-Saharan African Women: A Prospective Study. JMIR Mhealth Uhealth 2017;5:e72. [PMID: 28554879 DOI: 10.2196/mhealth.6697] [Cited by in Crossref: 8] [Cited by in F6Publishing: 7] [Article Influence: 1.6] [Reference Citation Analysis]
54 Okur E, Turkan M. A survey on automated melanoma detection. Engineering Applications of Artificial Intelligence 2018;73:50-67. [DOI: 10.1016/j.engappai.2018.04.028] [Cited by in Crossref: 30] [Cited by in F6Publishing: 8] [Article Influence: 7.5] [Reference Citation Analysis]
55 Subhi Y, Bube SH, Rolskov Bojsen S, Skou Thomsen AS, Konge L. Expert Involvement and Adherence to Medical Evidence in Medical Mobile Phone Apps: A Systematic Review. JMIR Mhealth Uhealth 2015;3:e79. [PMID: 26215371 DOI: 10.2196/mhealth.4169] [Cited by in Crossref: 54] [Cited by in F6Publishing: 36] [Article Influence: 7.7] [Reference Citation Analysis]
56 Jones OT, Jurascheck LC, van Melle MA, Hickman S, Burrows NP, Hall PN, Emery J, Walter FM. Dermoscopy for melanoma detection and triage in primary care: a systematic review. BMJ Open 2019;9:e027529. [PMID: 31434767 DOI: 10.1136/bmjopen-2018-027529] [Cited by in Crossref: 12] [Cited by in F6Publishing: 9] [Article Influence: 4.0] [Reference Citation Analysis]
57 Walter FM, Pannebakker MM, Barclay ME, Mills K, Saunders CL, Murchie P, Corrie P, Hall P, Burrows N, Emery JD. Effect of a Skin Self-monitoring Smartphone Application on Time to Physician Consultation Among Patients With Possible Melanoma: A Phase 2 Randomized Clinical Trial. JAMA Netw Open 2020;3:e200001. [PMID: 32101302 DOI: 10.1001/jamanetworkopen.2020.0001] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 3.5] [Reference Citation Analysis]
58 Yas QM, Zaidan AA, Zaidan BB, Hashim M, Lim CK. A Systematic Review on Smartphone Skin Cancer Apps: Coherent Taxonomy, Motivations, Open Challenges and Recommendations, and New Research Direction. J CIRCUIT SYST COMP 2018;27:1830003. [DOI: 10.1142/s0218126618300039] [Cited by in Crossref: 19] [Cited by in F6Publishing: 1] [Article Influence: 4.8] [Reference Citation Analysis]
59 Janda M, Soyer HP. Automated diagnosis of melanoma. Med J Aust 2017;207:361-2. [PMID: 29020911 DOI: 10.5694/mja17.00618] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 1.2] [Reference Citation Analysis]
60 Germine L, Reinecke K, Chaytor NS. Digital neuropsychology: Challenges and opportunities at the intersection of science and software. Clin Neuropsychol 2019;33:271-86. [PMID: 30614374 DOI: 10.1080/13854046.2018.1535662] [Cited by in Crossref: 40] [Cited by in F6Publishing: 33] [Article Influence: 13.3] [Reference Citation Analysis]